Gerdekoohi Shabnam Khorasani, Vosoughi Naser, Tanha Kaveh, Assadi Majid, Ghafarian Pardis, Rahmim Arman, Ay Mohammad Reza
Department of Energy Engineering, Sharif University of Technology, Tehran, Iran.
Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.
J Appl Clin Med Phys. 2017 Jul;18(4):215-223. doi: 10.1002/acm2.12094. Epub 2017 May 16.
Presence of photon attenuation severely challenges quantitative accuracy in single-photon emission computed tomography (SPECT) imaging. Subsequently, various attenuation correction methods have been developed to compensate for this degradation. The present study aims to implement an attenuation correction method and then to evaluate quantification accuracy of attenuation correction in small-animal SPECT imaging.
Images were reconstructed using an iterative reconstruction method based on the maximum-likelihood expectation maximization (MLEM) algorithm including resolution recovery. This was implemented in our designed dedicated small-animal SPECT (HiReSPECT) system. For accurate quantification, the voxel values were converted to activity concentration via a calculated calibration factor. An attenuation correction algorithm was developed based on the first-order Chang's method. Both phantom study and experimental measurements with four rats were used in order to validate the proposed method.
The phantom experiments showed that the error of -15.5% in the estimation of activity concentration in a uniform region was reduced to +5.1% when attenuation correction was applied. For in vivo studies, the average quantitative error of -22.8 ± 6.3% (ranging from -31.2% to -14.8%) in the uncorrected images was reduced to +3.5 ± 6.7% (ranging from -6.7 to +9.8%) after applying attenuation correction.
The results indicate that the proposed attenuation correction algorithm based on the first-order Chang's method, as implemented in our dedicated small-animal SPECT system, significantly improves accuracy of the quantitative analysis as well as the absolute quantification.
光子衰减的存在严重挑战了单光子发射计算机断层扫描（SPECT）成像中的定量准确性。随后，人们开发了各种衰减校正方法来弥补这种退化。本研究旨在实施一种衰减校正方法，然后评估小动物SPECT成像中衰减校正的定量准确性。
使用基于包括分辨率恢复的最大似然期望最大化（MLEM）算法的迭代重建方法重建图像。这在我们设计的专用小动物SPECT（HiReSPECT）系统中得以实现。为了进行准确的定量分析，通过计算校准因子将体素值转换为活度浓度。基于一阶张算法开发了一种衰减校正算法。为验证所提出的方法，进行了体模研究和对四只大鼠的实验测量。
体模实验表明，应用衰减校正后，均匀区域活度浓度估计中的-15.5%误差降低至+5.1%。对于体内研究，未校正图像中-22.8±6.3%（范围从-31.2%至-14.8%）的平均定量误差在应用衰减校正后降低至+3.5±6.7%（范围从-6.7至+9.8%）。
结果表明，在我们的专用小动物SPECT系统中实施的基于一阶张算法的所提出的衰减校正算法，显著提高了定量分析以及绝对定量的准确性。
